In a vehicle crash sensing and occupant protection system, multiple sensors may be used to determine the origin of the impact and other useful characteristics of the crash, to optimize the occupant restraining devices. As seen in FIG. 1, the stress waves from a vehicle impact propagate into the windshield glass in less than two milliseconds after impact, whereas the change in acceleration caused by the same impact is delayed by up to 20 milliseconds, as sensed by an accelerometer centrally located in the vehicle. The delayed response time of a central accelerometer is a severe constraint for inflatable occupant restraints (airbags), as the occupant may
have moved into the deployment space leading to injuries from the rapidly expanding device. The delay is particularly serious for side impact sensing, due to the limited space between the occupant and the door impact point.
The delayed response time of accelerometers has led others to propose installing sensors close to the point of impact, namely in front of the engine or on the door, but with the adverse consequences of reduced reliability, greater expense, and unneeded system complexity. Sensors located close to the point of impact often are destroyed by the impact, thus cutting off critical information. Locating crash sensors close to the point of impact has the effect of subjecting the sensors to environmental extremes, leading to possible failure. Accelerometers subjected to extreme heat and cold may need to be recalibrated as they age, causing inconvenience and expense to the owner and producer. Furthermore, since the vehicle designer does not know in advance exactly where an impact might occur, many sensors are required to cover all the possible impact locations. This sensor proliferation leads to reduced system reliability and greater expense, due to additional wiring, connectors, and attachment of the sensors. Further constraints are caused by the axial sensitivity of accelerometers, which require precise alignment with the vehicle axes. There is a need to locate the accelerometers at specific points in the vehicle; otherwise the desired sensitivity is compromised.
It is known that most materials change shape or form when subjected to stress, and the change may be evidenced in the material by other mechanisms. One such mechanism is an acoustic wave in which acoustic energy propagates through the material without affecting the integrity. One way for measuring acoustic waves is by using piezoelectric sensors adhered to a surface of the vehicle.
Polyvinylidene fluoride piezoelectric sensors (PVDF) are uniquely suited for the measurement of induced stresses ranging from bars to hundreds of kilo-bars. The PVDF sensors are thin (less than 25 μm). unobtrusive, self-powered, adaptable to complex contours, and available in a variety of configurations. PVDF thin-film piezoelectric polymer transducers can be employed over a wide range of stresses. Because the speed of sound in solid materials is much greater than the speed of sound in air, the acoustic waves generated by a crash arrive at the edge of a vehicle's windshield in a few microseconds after impact. Hence, it is believed that the windshield of the vehicle would be a good place to locate the PVDF sensors to receive acoustic wave propagation after an impact. Although the bonding material which adheres the windshield to the vehicle acts to dampen the waves, the energy content is sufficient to cross this barrier and propagate into the glass. Thus, PVDF sensors readily detect the spike from a crash event.
It is believed that uniform and fast response times can be achieved by applying the high bandwidth piezoelectric sensing material, preferably polyvinylidene fluoride (PVDF), in sensors located on the windshield glass. Published PCT application entitled “Omni-Directional Crash Sensor”, discloses a method for crash analysis employing geometric calculations based on inputs from multiple piezoelectric sensors applied to a vehicle transparency product such as the windshield. The piezoelectric material used in the sensor is polyvinylidene fluoride (PVDF). The PCT application also proposes methods of crash analysis employing signal spectrum analysis for at least two spectral frequencies. Reference is also made in this application to employing wavelets analysis for acoustic wave evaluation. The disclosure of this application is incorporated herein by reference.
Crash sensing algorithms for these distributed-sensor systems typically derive velocity or other measurements for each sensor and compare these to one or more thresholds. In some cases, the sensor response is decomposed into frequency bands with individual thresholds set for the centrally located accelerometer and the sensors on the periphery of the vehicle. These decision trees typically employ discrete analysis of inputs from the each of the sensors, and apply IF-AND-THEN logical operators to the separate data streams to arrive at a deploy decision. However, current technologies with airbag deployment in both the front and sides of the vehicle, in addition to two-stage airbag deployment, has rendered these algorithms too slow for adequate airbag deployment.
Because PVDF sensors possess very high bandwidth, they record vibrations or acoustic waves at frequencies not possible with accelerometers. That wide bandwidth contains information about many more modes of vibration that the windshield exhibits during crash and non-crash events. Those modes may be excited differently depending on the crash severity, direction, or other non-crash event, such as a rock hitting the windshield. Once the mode signals are separated, characteristics and differences between mode signals allows the determination of event conditions. Those techniques include time delay measurements, correlations, and interpeak delays. By subjecting the wave transmission received by the PVDF sensor to a wave analysis the modes of vibration may be separated according to transverse vs. longitudinal, rather than an arbitrary lower frequency threshold and arrival time of the acoustic wave. However, only a discrete analysis of each piezoelectric sensor input is possible because each sensor must be sampled and subjected to analysis on an individual basis. The aforementioned wavelet techniques do not involve successive analyses of a combination of sensory inputs to be obtained on a sample-by-sample basis, and using the result of the combination as the deciding factor in a crash analysis.
Thus, an unaddressed need exists in the industry to address the aforementioned deficiencies and inadequacies to analyze the input from multiple piezoelectric sensors which are located on the windshield of a vehicle.